How will AI impact on medicine?

Guest blog:Mercè Bonjorn Dalmau, University of Southern Denmark

William Osler (the father of modern medicine) said that "medicine is a science of uncertainty and an art of probability". And much has changed medicine since the beginning of the twentieth century.

Unpredictable?

It is true that medicine is not an exact science. There are many disparate factors: the biological reaction of each patient, almost always unpredictable to established protocols, interpretation of history and clinical evolution, therapeutic follow-up of the patient, and many other factors.

Art of the probable

Within the art of probability that Osler pointed out, the weighting of these factors makes the diagnosis or treatment of the patient accurate or not.

Each patient is a Big Data challenge

More and more medicine has become increasingly complex.

To the extent that it exceeds the capacity of the human mind.

We have more and more health data to ponder.

We have more and more therapies and diagnoses resulting from advances in immunology, genetics and systems biology.

More and more older patients, with more chronic diseases and more treatments.

There are more and more second opinions and more diagnostic tests.

More and more electronic health record (EHR) data are becoming available.

Medical decision making has become tremendously complex since each patient is a big challenge in managing big data.

And in the digital age, technology seems to be the way to the solution.

Its use in managing the complexity of 21st century medicine will require fundamental changes in the way we think about the thinking and structure of medical education and research.

The health of the future is at stake and the management "Big Data" has a lot to say about what the final result will be. This is where artificial intelligence comes in.

The limits of the human mind and the future of medicine

The limits of the human mind are evident and again technology can complement our decision-making. We currently have integrated disciplines such as cell biology and genetics in medical research and we need to advance similar efforts in artificial intelligence.

Then 21st century clinicians can have the tools they need to process data, make decisions, and master the complexity of 21st century patients. The time and exponential data is finite it is necessary to make ethical use of artificial intelligence (AI).Algorithms can systematically analyze every feature of any medical test. Deep learning requires time, good teaching, and inevitable corrections. Once tested and validated the algorithms could help us identify and treat the tens of thousands of patients under the same conditions. And also guide basic medical research on the mechanisms of newly discovered predictors.

Greatest technological challenge

AI is the greatest technological challenge in history that is not without ethical problems. Experts predict that the development of AI will give birth to a new generation of autonomous robots capable of meeting our needs and cover the knowledge that humans do not reach.

Artificial Intelligence in Health

AI is applicable in multiple sectors, and is clearly basic in the search for sustainable healthcare. Accessing and aggregating data in an intelligent way requires sophisticated AI applications and natural language processing (NLP).Large technology firms develop projects that accelerate the diagnosis of diseases. Examples of the use of artificial intelligence in health: the company CB Insights made a list in early 2017 of 106 health startups that use machine learning and predictive analytics, and the state of Artificial Intelligence. The dermatological algorithm for predicting Stanford skin cancer, Google's retinopathy system, the work of Enlitic in the detection of lung cancer and malignant classification, IBM Whatson Health algorism and others solutions emerging.

More questions than answers?

If artificial intelligence and big data is the solution, what is the question to the problem? Asking the right questions when designing the future is of vital importance. Any data analyst would say that a good analysis generates more questions than answers.

If our bodies are made of blood, water and data, could machines understand them better than human health professionals? Does automatic (robot) learning automate moral hazard and error? Will autonomous robots be a threat to the human race, as the films predict?

Health systems are often too slow to adapt to changes, and technological change in AI is exponential; how can we reconcile this? It will no longer be a matter of whether a physician should use AI, but if it is ethical if a doctor does not?

What is clear is that we are already in the future and technological progress is unstoppable. We are heading towards an increasingly connected and digitized world.

The use we make of the knowledge that is generated every day will lay the technological bases of the future and will also contribute to guarantee a higher quality of life and a much more efficient healthcare system.

Author: Mercè Bonjorn Dalmau Merbondal. Mercè is a WHINN AMBASSADOR, and PhD Research Fellow in CATCH_ITN Programme, Innovation Cancer Research and Connected eHealth.​